Simulating and Optimizing Hydrogen Production by Low-pressure Autothermal Reforming of Natural Gas using Non-dominated Sorting Genetic Algorithm-II

M. J. Azarhoosh, H. Ale Ebrahim and S. H. Pourtarah

Abstract
Conventional hydrogen production plants consist of natural gas steam reforming to CO+3H2 on Ni catalysts in a furnace, water-gas shift reaction for converting CO into CO2 and CO2 absorption. A new alternative method for highly endothermic steam reforming is autothermal reforming (steam reforming with air input to the reactor) without the need for external heating. In this study, hydrogen production by autothermal reforming for fuel cells (base case) was simulated based on a heterogeneous and one-dimensional model. In addition, the effect of operating variables on the system behavior was studied. Finally, Pareto-optimal solutions for the maximum molar flow rate of the produced hydrogen and methane conversion were determined by NSGA-II. There was a huge increase in the produced hydrogen molar flow to the base case, which showed the importance of optimizing autothermal reformers for hydrogen production.

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Keywords
simulation, multi-objective optimization, natural gas, hydrogen production, autothermal reforming, genetic algorithms